Polygons#

Download this notebook from GitHub (right-click to download).


import hvplot.pandas  # noqa

Using hvplot with geopandas is as simple as loading a geopandas dataframe and calling hvplot on it with geo=True.

import geopandas as gpd

countries = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
countries.sample(5)
pop_est continent name iso_a3 gdp_md_est geometry
123 1.071632e+07 Europe Greece GRC 209852 MULTIPOLYGON (((26.29000 35.29999, 26.16500 35...
139 1.397715e+09 Asia China CHN 14342903 MULTIPOLYGON (((109.47521 18.19770, 108.65521 ...
55 2.331072e+07 Africa Niger NER 12911 POLYGON ((14.85130 22.86295, 15.09689 21.30852...
77 6.855713e+06 Asia Lebanon LBN 51991 POLYGON ((35.82110 33.27743, 35.55280 33.26427...
71 1.862875e+07 Africa Malawi MWI 7666 POLYGON ((32.75938 -9.23060, 33.73972 -9.41715...
countries.hvplot(geo=True)

Control the color of the elements using the c option.

countries.hvplot.polygons(geo=True, c='pop_est', hover_cols='all')

You can even color by another series, such as population density:

countries.hvplot.polygons(geo=True, c=countries.pop_est/countries.area, clabel='pop density')
This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.

Download this notebook from GitHub (right-click to download).